The present embodiments relate to landmark (e.g. point, contours, surfaces, or volumes) detection. In particular, anatomy is detected in medical imaging.
Transesophogeal echocardiography scans the heart of a patient. The mitral valve may be of particular interest. The mitral valve, which ensures the uni-directional flow from the left atrium to the left ventricle, may suffer from insufficient closure. Insufficient closure allows blood to leak into the atrium during systole. For treatment, a catheter mounted implant is delivered to the mitral valve. The planning and/or performance for any mitral valve treatment may benefit from the detection and tracking of the mitral valve structures in medical imaging.
Detection of the mitral valve structures may be difficult due to the small size and rapid movement. Rather than the time consuming manual identification of the mitral valve structures, automated approaches may be used. Marginal space learning may be used to detect both the aortic and the mitral valves, but without consistent results for papillary landmarks. Mechanical constraints may be added, giving more robust leaflet tracking and identification of sub-valvular apparatus.
Semi-automatic mechanisms generally combine initial user input to identify the landmark in the image. The landmark is then tracked across the neighboring frames. In one semi-automatic approach, users have 20 planes in which the papillary muscles are manually identified. This approach is time consuming.
Intra-operative imaging is used to guide the mitral repair procedure. The detection may not operate sufficiently rapidly for real-time guidance. Despite the availability of real-time capable four-dimensional (i.e., three-dimensional space with time) imaging hardware, limited two-dimensional imaging and analysis of a single cardiac phase at a time is typically used. The mitral valve annulus may be detected in real-time for two-dimensional imaging, but with limited spatial resolution, with costly magnetic tracking hardware, and being limited to track on images of the same cardiac phase.